aceModerate evidence
Published recordHealthProblem Space
More
Psychological Outcomes and Correlates Associated with Over-Reliance on Artificial Intelligence Tools: An Integrative Review
- Truvace record
- TRV-2026-2519raw data (JSON)
- Version
- v1Published
- First published
- Evidence type
- Systematic review or meta-analysis
- Sources
- 1 sourcePeer-reviewed
- sha256
- d33d9a41edfa…check it
Abstract The growing use of artificial intelligence (AI) has raised concerns about over-reliance and its psychological implications. This integrative review synthesised psychological outcomes and correlates associated with AI over-reliance and examined its conceptualisation and measurement. The review included 28 studies identified through database and citation searching. AI over-reliance was associated with depression, anxiety, psychological distress, and cognitive disengagement, while findings concerning well-…
The problem
A review of 28 studies found AI over-reliance associated with depression, anxiety, psychological distress and cognitive disengagement, though mostly cross-sectional evidence cannot show it causes them.
What this doesn’t fix
Most included studies were cross-sectional self-report surveys, so they show associations only; sample representativeness and non-response bias were often unclear, and only one longitudinal study examined temporal direction.
Sources
1 on file- International Journal of Mental Health and Addictiondoi:10.1007/s11469-026-01724-1
Cite this record
v1Truvace Impact Record TRV-2026-2519, v1: “Psychological Outcomes and Correlates Associated with Over-Reliance on Artificial Intelligence Tools: An Integrative Review.” Truvace, 2026-11-12. /record/TRV-2026-2519 (accessed on the day you copy it). sha256 d33d9a41edfa3c4f…
Change history
1 versionEvery change made to this record since it was first published, and why. Nothing has changed since it went up.
Certified into the record
Check this record hasn’t been altered
How to check it yourself, without trusting this page
Download any version from /api/record/TRV-2026-2519 and hash its canonical field yourself, for example with shasum -a 256. You should get its content_hash. Each version’s text also ends with prev:and the hash of the version before it (version 1 points to 64 zeros). If anyone had changed a single character of any version after it was saved, those hashes wouldn’t line up.